1. Field of the Invention
The present invention relates to a fingerprint processing method and system for enhancing ridges of fingerprint images. More particularly, the present invention relates to the fingerprint processing method and system for enhancing ridges of fingerprint images utilizing a combination method of singular value decomposition (SVD) and wavelet transformation.
2. Description of the Related Art
Generally, the Henry Classification System was developed by Sir Edward Henry in British India in the late 19th century for sorting fingerprints by patterns, including a right loop, a left loop, a tented arch, a plain arch (i.e. arch) and a whorl. In addition, an eddy pattern and a twin loop pattern (i.e. S-type) are further classified into the pattern of whorls. However, the Henry Classification System is the basis of modern-day classification methods such as ridge flow classification approaches.
Taiwanese Patent Application Publication No. 200641700, entitled “Complete Reflection Type Fingerprint Identification Device,” discloses: a device including a main body, a light source, a connection body and an image sensor component. The main body has a finger-pressing zone, a first reflection zone and a light-transparent zone. Light beams from the light source penetrate through the light-transparent zone of the main body to irradiate a finger touch on the finger-pressing area. The connection body has a second reflection zone and the image sensor component is provided on the connection body. Provided between the main body and the connection body is a diaphragm which is a blacked, opaque eyelet diaphragm to filter stray light to form an image on the image sensor component which can capture a fingerprint image with a high degree of contrast and a low degree of noise (i.e., stray light).
Another Taiwanese Patent Publication No. 354397, entitled “Automatic classification method and systematical device for fingerprints,” discloses: a classification method and systematical device provided to sort input fingerprints by eights classifications according to numbers of core points and ridge flow directions therearound. First, an original image of the fingerprint is input and pretreated. A background portion and a fingerprint portion are retrieved from the original image according to means of gray scale and variances. In order to speed up the classification method, only the retrieved fingerprint portion is treated in the following steps. After retrieving the fingerprint portion, a mean directional value is calculated in each block of the fingerprint portion to generate a block directional image. Distributions of the block directional image are utilized to calculate positions of the core points. Finally, the input fingerprints are sort into eights classifications according to their core points and ridge flow directions.
However, there is a need of improving the fingerprint identification device disclosed in Taiwanese Patent Application Publication No. 200641700 and the automatic classification method and the systematical device disclosed in Taiwanese Patent Publication No. 354397 for enhancing ridges of the fingerprint images. The above-mentioned patent publications are incorporated herein by reference for purposes including, but not limited to, indicating the background of the present invention and illustrating the state of the art.
As is described in greater detail below, the present invention intends to provide a fingerprint processing method and a system for enhancing ridges of fingerprint images. An original fingerprint image is decomposed by a singular value decomposition method and a decomposed matrix of the original fingerprint image is transformed into a plurality of sub-band images by a discrete wavelet transformation method based on a Gussian template. The sub-band images are further compensated by a plurality of compensation weigh coefficients for enhancing ridges of fingerprint images in such a way as to mitigate and overcome the above problem.